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1.
Med Sci Monit ; 25: 2151-2158, 2019 Mar 23.
Article in English | MEDLINE | ID: mdl-30903656

ABSTRACT

BACKGROUND Osteoporosis affects millions of postmenopausal women worldwide. Invariant natural killer T cells (iNKT) are important cells for bone homeostasis. The sim of this study was to investigate the contribution of invariant natural killer T cells (iNKT) in the increased receptor activator of the nuclear factor-kappaB ligand (RANKL) pool and bone resorption, a characteristic of patients with osteoporosis. MATERIAL AND METHODS Whole blood was collected from 79 female patients. The dual energy x-absorptiometry scan was performed in all patients, and the T-score was calculated in order to classify our patients according to the World Human Organization (WHO) criteria for diagnosis and classification of osteoporosis. Eleven patients had a T-score -2.5 and were included in the osteoporosis group. We performed alpha-galactosylceramide activation of iNKT cells in vitro. Surface RANKL expression was detected by multicolor flow cytometry in naive and activated lymphocytes. Beta-Crosslaps (ß-CTx) levels were measured in whole blood plasma by ELISA (enzyme-linked immunosorbent assay). RESULTS Although iNKT cells were not clonally expanded in patients with osteoporosis, iNKT cells from osteoporotic patients overexpressed RANKL compared to ND and osteopenic patients. This is a distinctive feature of iNKT cells and is not seen in conventional T-lymphocytes. RANKL expression in iNKT cells was not related to ß-CTx levels in the blood. Finally, iNKT cell activation by the prototypal glycolipid ligand alpha-galactosylceramide increased by 8 times their RANKL expression. CONCLUSIONS In patients with osteoporosis, iNKT cells specifically overexpress RANKL, a cytokine that regulates osteoclast activity. It seems that iNKT cells have a long-standing effect of on the bone physiology, which plays an important role in the bone loss of patients with osteoporosis.


Subject(s)
Natural Killer T-Cells/metabolism , Osteoporosis/immunology , RANK Ligand/metabolism , Adult , Aged , Aged, 80 and over , Cytokines/metabolism , Female , Flow Cytometry , Glycolipids/metabolism , Humans , Lymphocyte Activation , Middle Aged , NF-kappa B/metabolism , RANK Ligand/genetics
2.
Med Sci Monit ; 24: 7665-7672, 2018 Oct 27.
Article in English | MEDLINE | ID: mdl-30367027

ABSTRACT

BACKGROUND The Nottingham Hip Fracture Score (NHFS) is validated as a predictive mortality tool in patients with hip fracture. However, it has not been modified or validated widely other than in the UK NHS health systems. MATERIAL AND METHODS We assessed the predictive capability of the NHFS for 30-day mortality after surgery for hip fracture in the Greek population and then compared the original model to a modified one. We applied the NHFS to the Greek population and created a modified model of the NHFS by including the New Mobility Score (NMS) (Parker and Palmer, 1993) to the evaluated parameters and excluding the parameter of institution. We ran a prospective study over a period of 3 years in our institution, collecting full data from 349 patients. All data were analyzed using SPSS, version 20. RESULTS From all 349 patients, with a mean age of 80.82 years, only 85 (24.4%) were men. All patients were followed up for at least 30 days and the NHFS and modified NHFS prediction were compared with the mortality rate of patients. The area under the ROC curve for both models suggested acceptable accuracy (original NHFS 0.83, modified NHFS 0.84). Calibration was acceptable for both models (Hosmer-Lemeshow p=0.31 and 0.11, respectively). CONCLUSIONS Both the original and the modified NHFS were significant predictors of 30-day mortality. A higher-power study might be able to show superiority of the modified one for the Greek population in the future.


Subject(s)
Hip Fractures/mortality , Risk Assessment/methods , Aged , Aged, 80 and over , Decision Support Techniques , Female , Greece , Hip Fractures/surgery , Hospital Mortality , Humans , Male , Pelvic Bones/injuries , Pelvic Bones/surgery , Prospective Studies , ROC Curve , Reproducibility of Results , Risk Factors , Sensitivity and Specificity
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